Conviction Delegation

A core challenge is the activation energy required for voters to re-delegate. Once a user delegates their voting power, they may become passive, allowing their conviction to accumulate with a delegate whose views or performance may have changed. This creates governance inertia, where outdated or misaligned voting power persists in the system, potentially skewing outcomes. Platforms must design clear alerts and simple re-delegation flows to combat this.

The system can inadvertently lead to power concentration in a few popular delegates, mirroring Proof-of-Stake validator centralization. Key risks include:

• Whale Influence: A single large token holder delegating to one entity can create a dominant voting bloc.
• Cartel Formation: Delegates may form alliances, reducing genuine competition and debate.
• Single Point of Failure: The decision-making process becomes vulnerable to the corruption or coercion of a few key delegates.

Conviction systems are vulnerable to Sybil attacks, where a single entity creates many pseudonymous identities (Sybils) to accumulate delegations and influence. Mitigating this requires robust identity verification or reputation systems, which themselves introduce complexity and potential for exclusion. Without such guards, the system's security and legitimacy are compromised, as voting power does not reflect unique human or stakeholder alignment.

Designing the right incentives for both delegates and delegators is non-trivial. Poor design can lead to misaligned rewards. Considerations include:

• Should delegates be compensated, and if so, how (direct fees, token rewards)?
• Does compensation create a professional delegate class that may prioritize income over protocol health?
• How to prevent vote buying or other forms of incentive manipulation that undermine the conviction model's intent?

Delegators often lack the time or expertise to fully evaluate a delegate's track record, proposals, and conflicts of interest. This information asymmetry can lead to suboptimal delegation choices based on popularity or marketing rather than merit. Effective systems require transparent delegate profiles, voting histories, and statement-of-intent platforms to reduce this gap and enable informed principal-agent relationships.

Locking tokens to build conviction represents a significant opportunity cost for the delegator. Those tokens cannot be used for yield farming, collateral, or trading elsewhere. The required lock-up period must be carefully calibrated: too short and it fails to signal long-term commitment; too long and it discourages participation. This tension between signaling strength and capital flexibility is a fundamental economic constraint of the model.

A foundational mechanism where a user's voting power is directly proportional to the length of time their tokens are locked in a governance contract. This creates a cost for rapid opinion changes and aligns voter incentives with long-term protocol health.

• Mechanism: Power often increases linearly or logarithmically with lock duration.
• Purpose: Mitigates flash loan attacks and sybil attacks by making vote-buying expensive.
• Example: A user locking tokens for 4 years may have 4x the voting power of someone locking for 1 year.

A prediction market-enhanced governance model that uses conviction voting to signal demand for a proposal before a full vote. It allows a minority with strong conviction to fast-track proposals, improving efficiency.

• Process: Stake tokens on a proposal to increase its 'conviction' score; once a threshold is met, it moves to a final vote.
• Benefit: Filters out low-interest proposals and surfaces those with dedicated support.
• Origin: Pioneered by the DAOstack ecosystem as a scalability solution for decentralized governance.

A voting system where the cost of acquiring additional votes on a single issue increases quadratically. While distinct from time-based conviction, it shares the goal of measuring intensity of preference and limiting whale dominance.

• Formula: Cost = (Number of Votes)². Buying 2 votes costs 4 credits, 3 votes costs 9 credits.
• Contrast with Conviction: Quadratic voting measures preference intensity within a single election; conviction measures commitment over time across multiple cycles.
• Use Case: Effectively used for Gitcoin Grants funding rounds to democratize allocation.

A blockchain consensus and governance model where token holders vote to elect a small set of validators or witnesses to produce blocks and govern on their behalf. It introduces delegation but typically without a time-based conviction mechanism.

• Key Difference: In DPoS, delegation is binary (elect a representative). In conviction delegation, power is earned continuously and can be directed to specific proposals.
• Examples: EOS, TRON, and Cosmos hubs use variations of DPoS for both consensus and governance.

A governance paradigm proposed by economist Robin Hanson where markets are used to make decisions. Voters bet on prediction markets tied to measurable outcomes, and the policy expected to produce the best result is implemented.

• Relation to Conviction: Both use market-like mechanisms (staking, betting) to quantify belief and commitment. Futarchy measures expected value, while conviction measures duration of support.
• Process: 1) Vote on a metric of success (e.g., token price). 2) Markets trade on which proposal will better improve that metric.

A safety mechanism allowing members to exit a Decentralized Autonomous Organization (DAO) and withdraw their proportional share of assets if they disagree with a passed proposal. This creates a direct cost for poor governance decisions.

• Interaction with Conviction: While not a conviction system itself, ragequit complements time-based voting by providing a final check. A member's long-term conviction (via staking) can be instantly revoked if the DAO acts against their interests, imposing a real cost on the collective.